conftrace_

gradient descent

1144 papers

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Also known as

GD

Co-occurring keywords

neural network (6616) neural network optimization (1293) convex optimization (1321) non-convex optimization (547) convergence rate (607) stochastic optimization (1060) convergence analysis (395) stochastic gradient descent (1091) nonconvex optimization (316) implicit bia (107)

Papers

Early Alignment in Two-Layer Networks Training is a Two-Edged Sword JMLR 2025
Learning Complexity of Gradient Descent and Conjugate Gradient Algorithms AAAI 2025
General Loss Functions Lead to (Approximate) Interpolation in High Dimensions JMLR 2025
Corpus Poisoning via Approximate Greedy Gradient Descent ACL 2025
DiffIM: Differentiable Influence Minimization with Surrogate Modeling and Continuous Relaxation AAAI 2025
Balanced Rate-Distortion Optimization in Learned Image Compression CVPR 2025
AdamS: Momentum Itself Can Be A Normalizer for LLM Pretraining and Post-training EMNLP 2025
Optimization Over a Probability Simplex JMLR 2025
LUSD: Localized Update Score Distillation for Text-Guided Image Editing ICCV 2025
Learning to Generate Gradients for Test-Time Adaptation via Test-Time Training Layers AAAI 2025
CompAct: Compressed Activations for Memory-Efficient LLM Training NAACL 2025
DUTir at SemEval-2025 Task 4: Optimized Fine-Tuning of Linear Layers for Balanced Knowledge Forgetting and Retention SEMEVAL 2025
Boosting Causal Additive Models JMLR 2025
GFPack++: Attention-Driven Gradient Fields for Optimizing 2D Irregular Packing ICCV 2025
PSMGD: Periodic Stochastic Multi-Gradient Descent for Fast Multi-Objective Optimization AAAI 2025
Unlearning Concepts in Diffusion Model via Concept Domain Correction and Concept Preserving Gradient AAAI 2025
Gradient-Based Sample Selection for Black-Box Universal Domain Adaptation AAAI 2025
Task-Specific Preconditioner for Cross-Domain Few-Shot Learning AAAI 2025
Unity in Diversity: Video Editing via Gradient-Latent Purification CVPR 2025
Random Pruning Over-parameterized Neural Networks Can Improve Generalization: A Training Dynamics Analysis JMLR 2025
From Logistic Regression to the Perceptron Algorithm: Exploring Gradient Descent with Large Step Sizes AAAI 2025
Tilted Quantile Gradient Updates for Quantile-Constrained Reinforcement Learning AAAI 2025
Full Parameter Fine-tuning for Large Language Models with Limited Resources ACL 2024
On Mesa-Optimization in Autoregressively Trained Transformers: Emergence and Capability NIPS 2024
Gradient Reweighting: Towards Imbalanced Class-Incremental Learning CVPR 2024